Query elasticsearch to make all analyzed ngram tokens to match - elasticsearch

Question

I indexed some data using a nGram analyzer (which emits only tri-grams), to solve the compound words problem exactly as described at the ES guide.
This doesn't work however as expected: the according match query will return all documents where at least one nGram-token (per word) matched.
Example:
Let's take these two indexed documents with a single field, using that nGram analyzer:
POST /compound_test/doc/_bulk
{ "index": { "_id": 1 }}
{ "content": "elasticsearch is awesome" }
{ "index": { "_id": 2 }}
{ "content": "some search queries don't perform good" }
Now if I run the following query, I get both results:
"match": {
"content": {
"query": "awesome search",
"minimum_should_match": "100%"
}
}
The query that is constructed from this, could be expressed like this:
(awe OR wes OR eso OR ome) AND (sea OR ear OR arc OR rch)
That's why the second document matches (it contains "some" and "search"). It would even match a document with words that contain the tokens "som" and "rch".
What I actually want is a query where each analyzed token must match (in the best case depending on the minimum-should-match), so something like this:
"match": {
"content": {
"query": "awe wes eso ome sea ear arc rch",
"analyzer": "whitespace",
"minimum_should_match": "100%"
}
}
..without actually creating that query "from hand" / pre-analyzing it on client side.
All settings and data to reproduce that behavior can be found at https://pastebin.com/97QxfaSb
Is there such a possibility?

Answer 1

While writing the question, I accidentally found the answer:
If the ngram analyzer uses a ngram-filter to generate trigrams (as described in the guide), it works the way described above. (I guess because the actual tokens are not the single ngrams but the combination of all created ngrams)
To achieve the wanted behavior, the analyzer must use the ngram tokenizer:
"tokenizer": {
"trigram_tokenizer": {
"type": "ngram",
"min_gram": 3,
"max_gram": 3,
"token_chars": [
"letter",
"digit"
]
}
},
"analyzer": {
"trigrams_with_tokenizer": {
"type": "custom",
"tokenizer": "trigram_tokenizer"
}
}
Using this way to produce tokens will result in the wished result when queering that field.